# -*- coding: utf-8 -*-
"""
Creates the plot in the bspline-fortran logo.
This is the data from the `test_regrid` unit test program.
"""

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np

fig = plt.figure(figsize=[10,10],facecolor='white')
ax = fig.add_subplot(111, projection='3d')
ax._axis3don = False


#x = range(0,11)
#y = range(0,9)
x = [ 0.000000,  0.100000,  0.200000,  0.300000,  0.400000,  0.500000,  0.600000,  0.700000,  0.800000,  0.900000,  1.000000,  1.100000,  1.200000,  1.300000,  1.400000,  1.500000,  1.600000,  1.700000,  1.800000,  1.900000,  2.000000,  2.100000,  2.200000,  2.300000,  2.400000,  2.500000,  2.600000,  2.700000,  2.800000,  2.900000,  3.000000,  3.100000,  3.200000,  3.300000,  3.400000,  3.500000,  3.600000,  3.700000,  3.800000,  3.900000,  4.000000,  4.100000,  4.200000,  4.300000,  4.400000,  4.500000,  4.600000,  4.700000,  4.800000,  4.900000,  5.000000,  5.100000,  5.200000,  5.300000,  5.400000,  5.500000,  5.600000,  5.700000,  5.800000,  5.900000,  6.000000,  6.100000,  6.200000,  6.300000,  6.400000,  6.500000,  6.600000,  6.700000,  6.800000,  6.900000,  7.000000,  7.100000,  7.200000,  7.300000,  7.400000,  7.500000,  7.600000,  7.700000,  7.800000,  7.900000,  8.000000,  8.100000,  8.200000,  8.300000,  8.400000,  8.500000,  8.600000,  8.700000,  8.800000,  8.900000,  9.000000,  9.100000,  9.200000,  9.300000,  9.400000,  9.500000,  9.600000,  9.700000,  9.800000,  9.900000]
y = [ 0.000000,  0.100000,  0.200000,  0.300000,  0.400000,  0.500000,  0.600000,  0.700000,  0.800000,  0.900000,  1.000000,  1.100000,  1.200000,  1.300000,  1.400000,  1.500000,  1.600000,  1.700000,  1.800000,  1.900000,  2.000000,  2.100000,  2.200000,  2.300000,  2.400000,  2.500000,  2.600000,  2.700000,  2.800000,  2.900000,  3.000000,  3.100000,  3.200000,  3.300000,  3.400000,  3.500000,  3.600000,  3.700000,  3.800000,  3.900000,  4.000000,  4.100000,  4.200000,  4.300000,  4.400000,  4.500000,  4.600000,  4.700000,  4.800000,  4.900000,  5.000000,  5.100000,  5.200000,  5.300000,  5.400000,  5.500000,  5.600000,  5.700000,  5.800000,  5.900000,  6.000000,  6.100000,  6.200000,  6.300000,  6.400000,  6.500000,  6.600000,  6.700000,  6.800000,  6.900000,  7.000000,  7.100000,  7.200000,  7.300000,  7.400000,  7.500000,  7.600000,  7.700000,  7.800000,  7.900000]


X, Y = np.meshgrid(x, y)

z=np.array([[ 0.000000, 0.202909, 0.384567, 0.545754, 0.687250, 0.809834, 0.914285, 1.001385, 1.071911, 1.126644, 1.166363, 1.191847, 1.203877, 1.203232, 1.190692, 1.167035, 1.133042, 1.089492, 1.037165, 0.976840, 0.909297, 0.835316, 0.755676, 0.671156, 0.582537, 0.490598, 0.396117, 0.299876, 0.202654, 0.105229, 0.008383,-0.087107,-0.180459,-0.270895,-0.357635,-0.439900,-0.516909,-0.587883,-0.652044,-0.708610,-0.756802,-0.796032,-0.826467,-0.848466,-0.862389,-0.868593,-0.867438,-0.859282,-0.844484,-0.823403,-0.796398,-0.763826,-0.726048,-0.683421,-0.636305,-0.585058,-0.530039,-0.471606,-0.410119,-0.345936,-0.279415,-0.210917,-0.140798,-0.069418, 0.002863, 0.075689, 0.148699, 0.221535, 0.293839, 0.365251, 0.435413, 0.503967, 0.570553, 0.634812, 0.696386, 0.754917, 0.810045, 0.861412, 0.908659, 0.951427],
[ 0.202164, 0.379337, 0.536154, 0.673400, 0.791859, 0.892313, 0.975546, 1.042344, 1.093488, 1.129764, 1.151954, 1.160843, 1.157215, 1.141852, 1.115540, 1.079061, 1.033200, 0.978740, 0.916466, 0.847160, 0.771607, 0.690590, 0.604894, 0.515301, 0.422597, 0.327564, 0.230986, 0.133648, 0.036332,-0.060177,-0.155095,-0.247639,-0.337025,-0.422469,-0.503187,-0.578396,-0.647312,-0.709151,-0.763129,-0.808462,-0.844367,-0.870272,-0.886451,-0.893390,-0.891575,-0.881494,-0.863631,-0.838474,-0.806508,-0.768220,-0.724096,-0.674623,-0.620285,-0.561570,-0.498965,-0.432954,-0.364024,-0.292663,-0.219355,-0.144587,-0.068845, 0.007384, 0.083614, 0.159359, 0.234133, 0.307450, 0.378823, 0.447766, 0.513793, 0.576417, 0.635153, 0.689514, 0.739014, 0.783167, 0.821486, 0.853485, 0.878678, 0.896579, 0.906702, 0.908560],
[ 0.383192, 0.535423, 0.668298, 0.782599, 0.879105, 0.958597, 1.021854, 1.069658, 1.102788, 1.122024, 1.128147, 1.121937, 1.104175, 1.075640, 1.037113, 0.989374, 0.933203, 0.869381, 0.798688, 0.721904, 0.639810, 0.553185, 0.462810, 0.369466, 0.273932, 0.176988, 0.079416,-0.018006,-0.114495,-0.209273,-0.301559,-0.390573,-0.475534,-0.555663,-0.630178,-0.698300,-0.759248,-0.812243,-0.856504,-0.891250,-0.915701,-0.929308,-0.932436,-0.925684,-0.909648,-0.884925,-0.852113,-0.811808,-0.764607,-0.711108,-0.651908,-0.587603,-0.518791,-0.446069,-0.370033,-0.291282,-0.210411,-0.128018,-0.044700, 0.038946, 0.122322, 0.204833, 0.285881, 0.364868, 0.441198, 0.514273, 0.583498, 0.648273, 0.708004, 0.762091, 0.809940, 0.850951, 0.884529, 0.910076, 0.926995, 0.934690, 0.932563, 0.920016, 0.896454, 0.861279],
[ 0.543857, 0.671952, 0.781790, 0.874138, 0.949767, 1.009446, 1.053945, 1.084033, 1.100480, 1.104054, 1.095526, 1.075664, 1.045239, 1.005020, 0.955775, 0.898276, 0.833290, 0.761589, 0.683940, 0.601113, 0.513879, 0.423006, 0.329263, 0.233421, 0.136249, 0.038516,-0.059009,-0.155555,-0.250354,-0.342636,-0.431632,-0.516572,-0.596686,-0.671206,-0.739361,-0.800383,-0.853501,-0.897947,-0.932951,-0.957744,-0.971555,-0.973860,-0.965106,-0.945985,-0.917190,-0.879412,-0.833343,-0.779674,-0.719099,-0.652307,-0.579993,-0.502846,-0.421560,-0.336826,-0.249335,-0.159781,-0.068854, 0.022754, 0.114350, 0.205243, 0.294740, 0.382151, 0.466783, 0.547944, 0.624943, 0.697087, 0.763685, 0.824044, 0.877474, 0.923282, 0.960776, 0.989264, 1.008054, 1.016456, 1.013776, 0.999323, 0.972404, 0.932329, 0.878406, 0.809941],
[ 0.684934, 0.789713, 0.877419, 0.948804, 1.004621, 1.045621, 1.072555, 1.086176, 1.087235, 1.076484, 1.054675, 1.022559, 0.980890, 0.930417, 0.871894, 0.806071, 0.733701, 0.655536, 0.572327, 0.484826, 0.393785, 0.299956, 0.204090, 0.106939, 0.009256,-0.088208,-0.184702,-0.279473,-0.371770,-0.460841,-0.545933,-0.626296,-0.701178,-0.769826,-0.831489,-0.885415,-0.930853,-0.967049,-0.993254,-1.008714,-1.012678,-1.004649,-0.985143,-0.954932,-0.914788,-0.865481,-0.807783,-0.742466,-0.670300,-0.592058,-0.508511,-0.420429,-0.328585,-0.233749,-0.136694,-0.038190, 0.060992, 0.160079, 0.258300, 0.354885, 0.449061, 0.540057, 0.627103, 0.709426, 0.786255, 0.856819, 0.920347, 0.976067, 1.023207, 1.060997, 1.088664, 1.105439, 1.110548, 1.103221, 1.082687, 1.048174, 0.998911, 0.934126, 0.853048, 0.754906],
[ 0.807195, 0.889489, 0.955977, 1.007386, 1.044444, 1.067879, 1.078419, 1.076791, 1.063723, 1.039943, 1.006179, 0.963158, 0.911608, 0.852257, 0.785833, 0.713063, 0.634675, 0.551397, 0.463957, 0.373082, 0.279500, 0.183940, 0.087128,-0.010208,-0.107339,-0.203538,-0.298078,-0.390230,-0.479267,-0.564461,-0.645085,-0.720409,-0.789708,-0.852253,-0.907315,-0.954169,-0.992085,-1.020336,-1.038194,-1.044932,-1.039822,-1.022396,-0.993230,-0.953161,-0.903024,-0.843657,-0.775894,-0.700574,-0.618530,-0.530601,-0.437622,-0.340429,-0.239859,-0.136748,-0.031932, 0.073753, 0.179470, 0.284383, 0.387656, 0.488452, 0.585936, 0.679272, 0.767622, 0.850150, 0.926021, 0.994399, 1.054446, 1.105327, 1.146205, 1.176244, 1.194609, 1.200462, 1.192967, 1.171289, 1.134591, 1.082036, 1.012789, 0.926013, 0.820872, 0.696530],
[ 0.911415, 0.972069, 1.018255, 1.050671, 1.070014, 1.076982, 1.072274, 1.056585, 1.030616, 0.995062, 0.950622, 0.897994, 0.837876, 0.770964, 0.697958, 0.619554, 0.536451, 0.449346, 0.358937, 0.265921, 0.170997, 0.074862,-0.021786,-0.118249,-0.213829,-0.307830,-0.399552,-0.488299,-0.573372,-0.654074,-0.729707,-0.799573,-0.862974,-0.919214,-0.967593,-1.007415,-1.037981,-1.058594,-1.068555,-1.067168,-1.053735,-1.027821,-0.990050,-0.941309,-0.882485,-0.814466,-0.738138,-0.654389,-0.564106,-0.468176,-0.367487,-0.262924,-0.155377,-0.045731, 0.065126, 0.176307, 0.286925, 0.396092, 0.502922, 0.606527, 0.706020, 0.800513, 0.889121, 0.970955, 1.045128, 1.110753, 1.166944, 1.212812, 1.247471, 1.270033, 1.279612, 1.275320, 1.256270, 1.221574, 1.170347, 1.101699, 1.014745, 0.908598, 0.782369, 0.635172],
[ 0.998366, 1.038238, 1.065044, 1.079446, 1.082107, 1.073689, 1.054854, 1.026265, 0.988582, 0.942470, 0.888590, 0.827604, 0.760175, 0.686964, 0.608635, 0.525849, 0.439268, 0.349556, 0.257373, 0.163383, 0.068247,-0.027373,-0.122813,-0.217412,-0.310507,-0.401437,-0.489538,-0.574150,-0.654609,-0.730253,-0.800420,-0.864449,-0.921675,-0.971438,-1.013075,-1.045924,-1.069323,-1.082608,-1.085119,-1.076193,-1.055168,-1.021645,-0.976285,-0.920014,-0.853755,-0.778434,-0.694976,-0.604305,-0.507346,-0.405025,-0.298265,-0.187992,-0.075131, 0.039394, 0.154658, 0.269736, 0.383702, 0.495633, 0.604603, 0.709688, 0.809963, 0.904502, 0.992381, 1.072676, 1.144461, 1.206812, 1.258803, 1.299510, 1.328008, 1.343372, 1.344677, 1.330999, 1.301413, 1.254993, 1.190816, 1.107955, 1.005487, 0.882486, 0.738028, 0.571188],
[ 1.068823, 1.088783, 1.097135, 1.094501, 1.081502, 1.058760, 1.026897, 0.986535, 0.938294, 0.882798, 0.820666, 0.752522, 0.678987, 0.600682, 0.518230, 0.432251, 0.343367, 0.252201, 0.159373, 0.065506,-0.028779,-0.122860,-0.216116,-0.307925,-0.397665,-0.484714,-0.568452,-0.648255,-0.723503,-0.793574,-0.857847,-0.915699,-0.966508,-1.009654,-1.044515,-1.070468,-1.086893,-1.093167,-1.088669,-1.072778,-1.044871,-1.004588,-0.952619,-0.889912,-0.817418,-0.736087,-0.646868,-0.550712,-0.448568,-0.341386,-0.230117,-0.115710, 0.000885, 0.118718, 0.236839, 0.354298, 0.470146, 0.583431, 0.693205, 0.798517, 0.898418, 0.991958, 1.078185, 1.156152, 1.224907, 1.283502, 1.330985, 1.366407, 1.388818, 1.397268, 1.390808, 1.368486, 1.329354, 1.272462, 1.196859, 1.101595, 0.985721, 0.848287, 0.688342, 0.504938],
[ 1.123559, 1.124490, 1.115318, 1.096621, 1.068974, 1.032954, 0.989138, 0.938101, 0.880421, 0.816674, 0.747436, 0.673284, 0.594794, 0.512543, 0.427107, 0.339062, 0.248986, 0.157455, 0.065044,-0.027669,-0.120108,-0.211697,-0.301858,-0.390016,-0.475595,-0.558017,-0.636706,-0.711086,-0.780581,-0.844613,-0.902607,-0.953985,-0.998172,-1.034591,-1.062665,-1.081818,-1.091474,-1.091056,-1.079988,-1.057692,-1.023594,-0.977372,-0.919734,-0.851642,-0.774060,-0.687950,-0.594277,-0.494002,-0.388089,-0.277502,-0.163203,-0.046156, 0.072677, 0.192332, 0.311847, 0.430257, 0.546600, 0.659913, 0.769232, 0.873595, 0.972039, 1.063599, 1.147314, 1.222220, 1.287354, 1.341752, 1.384452, 1.414491, 1.430904, 1.432731, 1.419006, 1.388767, 1.341051, 1.274895, 1.189336, 1.083409, 0.956154, 0.806605, 0.633801, 0.436778],
[ 1.163347, 1.146145, 1.120386, 1.086595, 1.045302, 0.997031, 0.942312, 0.881670, 0.815634, 0.744729, 0.669483, 0.590423, 0.508077, 0.422971, 0.335632, 0.246588, 0.156365, 0.065491,-0.025507,-0.116103,-0.205768,-0.293977,-0.380202,-0.463915,-0.544590,-0.621700,-0.694717,-0.763115,-0.826366,-0.883944,-0.935321,-0.979970,-1.017364,-1.046976,-1.068279,-1.080745,-1.083849,-1.077062,-1.059857,-1.031708,-0.992088,-0.940717,-0.878313,-0.805840,-0.724264,-0.634550,-0.537662,-0.434567,-0.326228,-0.213612,-0.097683, 0.020593, 0.140252, 0.260328, 0.379857, 0.497872, 0.613410, 0.725504, 0.833190, 0.935503, 1.031477, 1.120147, 1.200549, 1.271717, 1.332686, 1.382491, 1.420167, 1.444748, 1.455270, 1.450767, 1.430275, 1.392828, 1.337461, 1.263209, 1.169107, 1.054190, 0.917493, 0.758049, 0.574896, 0.367066],
[ 1.188962, 1.154536, 1.113127, 1.065211, 1.011262, 0.951752, 0.887156, 0.817948, 0.744602, 0.667592, 0.587392, 0.504476, 0.419318, 0.332392, 0.244171, 0.155130, 0.065743,-0.023516,-0.112174,-0.199756,-0.285789,-0.369798,-0.451309,-0.529849,-0.604943,-0.676118,-0.742899,-0.804813,-0.861385,-0.912143,-0.956610,-0.994315,-1.024782,-1.047538,-1.062109,-1.068021,-1.064799,-1.051970,-1.029060,-0.995596,-0.951102,-0.895343,-0.829038,-0.753143,-0.668615,-0.576411,-0.477486,-0.372797,-0.263302,-0.149956,-0.033717, 0.084459, 0.203617, 0.322798, 0.441046, 0.557406, 0.670919, 0.780631, 0.885583, 0.984820, 1.077385, 1.162321, 1.238671, 1.305481, 1.361791, 1.406647, 1.439091, 1.458166, 1.462917, 1.452387, 1.425619, 1.381656, 1.319542, 1.238321, 1.137035, 1.014728, 0.870444, 0.703226, 0.512117, 0.296161],
[ 1.201176, 1.150447, 1.094335, 1.033257, 0.967631, 0.897875, 0.824405, 0.747640, 0.667998, 0.585894, 0.501749, 0.415978, 0.328999, 0.241230, 0.153089, 0.064993,-0.022640,-0.109394,-0.194849,-0.278589,-0.360197,-0.439254,-0.515342,-0.588046,-0.656946,-0.721625,-0.781666,-0.836651,-0.886163,-0.929784,-0.967096,-0.997683,-1.021125,-1.037006,-1.044909,-1.044415,-1.035108,-1.016568,-0.988380,-0.950125,-0.901386,-0.841971,-0.772593,-0.694189,-0.607699,-0.514059,-0.414209,-0.309086,-0.199629,-0.086776, 0.028535, 0.145365, 0.262777, 0.379832, 0.495592, 0.609118, 0.719473, 0.825719, 0.926916, 1.022128, 1.110415, 1.190839, 1.262463, 1.324348, 1.375555, 1.415148, 1.442186, 1.455733, 1.454849, 1.438598, 1.406040, 1.356237, 1.288251, 1.201144, 1.093978, 0.965814, 0.815715, 0.642742, 0.445956, 0.224420],
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)
z = np.transpose(z)

ax.plot_wireframe(X,Y,z, rcount=90, ccount=90 )

ax.patch.set_facecolor('white')
ax.patch.set_alpha(0.0)

ax.get_xaxis().set_visible(False) # this removes the ticks and numbers for x axis
ax.get_yaxis().set_visible(False) # this removes the ticks and numbers for y axis

fig.savefig('spline.svg',transparent=True, bbox_inches='tight',pad_inches = 0, dpi = 300)